Airweave

We're looking for a Founding Forward Deployed Engineer to work directly with our most important customers, including one of the world's leading AI labs, and make Airweave work in their environments. This is not a support role. Forward deployed means you're the bridge between what we've built and what customers actually need. You'll be embedded with enterprise teams, understanding their infrastructure, data sources, and constraints. You'll solve problems that turn into product features. You'll spend time on-site with enterprises, ship code that solves their specific problems, and make sure Airweave delivers in environments we've never seen. The work spans Kubernetes, Python, PostgreSQL, and LLM infrastructure, but the real skill is figuring out how it all fits together somewhere new. This is crucial early-stage work. Your work will directly determine how we land and expand in enterprise. What you'll work on Deploy and integrate Airweave into enterprise environments: on-prem, hybrid cloud, air-gapped networks Build custom connectors and integrations for customer-specific data sources and workflows Debug production issues in real time, often on customer infrastructure Work directly with technical teams at customers, including to understand their requirements and constraints Translate customer feedback into product improvements; you'll have a direct line to engineering Own the technical relationship with key accounts from proof-of-concept through production Build the playbooks and tooling that define how Airweave lands in enterprise Always free to contribute directly to the Airweave product based on what you learn in the field Travel to customer sites across Europe as needed You might be a fit if You're comfortable working directly with customers and can communicate technical concepts clearly at the whiteboard You've deployed software in enterprise environments and understand the realities (security reviews, network constraints, compliance) You're a strong generalist: comfortable with Python, infrastructure, databases, and whatever else the problem requires You thrive in ambiguity and can figure things out without a playbook You can debug distributed systems under moderate pressure: logs, traces, intuition and teamwork You're willing to travel and work on-site with customers when needed Bonus points: Experience with data/LLM infrastructure deployments Background in solutions engineering, technical leadership, or customer-facing technical roles Familiarity with enterprise security requirements (SOC 2, GDPR, on-prem deployments) French, German or Dutch language skills What we offer Customers including one of the world's leading AI labs Competitive salary (€80K–€100K) with meaningful equity (0.25%–0.75%) Work in-person in the heart of Amsterdam (Herengracht) with a highly-skilled, technical team Direct line to product and engineering: your insights shape what we build

We're looking for a founding engineer to own Airweave's data and infrastructure layer, the systems that make our distributed search and data pipelines scalable, reliable and observable. At Airweave, you'll build and operate the platform that thousands of AI agents depend on. That means distributed sync pipelines pulling data from dozens of sources, vector databases powering LLM search, and the orchestration layer that keeps it all running. You'll work closely with the product team, but your focus is on the foundation: making sure data flows reliably at scale, LLM inference stays fast, and the whole system holds up under real production load. This is early-stage infrastructure work. The architecture is still being shaped, and your decisions will define how we scale. What you'll work on Design and scale distributed data pipelines that sync hundreds of millions of documents from dozens sources into advanced search indexes Build and improve Temporal workflows for parallel sync orchestration: retries, backpressure, and failure recovery across workers Own our Kubernetes deployments with Helm charts: autoscaling, and resource management for bursty search, sync and LLM workloads Scale PostgreSQL for high-throughput; connection pooling, read replicas, partitioning (we ask a lot from this database) Manage vector database (Vespa) infrastructure: sharding, replication, backup strategies for large-scale agentic search Orchestrate and optimize LLM inference pipelines: batching, caching, provider failover Build monitoring and alerting with Prometheus, Grafana, and custom instrumentation for cluster health Infrastructure as code for the base with Terraform You might be a fit if You've built or operated data pipelines at scale: ETL, event processing, streaming, or sync infrastructure You're comfortable with Kubernetes, Terraform, and infrastructure as code You've scaled databases and understand the tradeoffs (pooling, replication, sharding) You have experience with distributed systems: workflow orchestration, message queues, eventual consistency You're interested in LLM infrastructure: embeddings, vector search, inference optimization You like building reliable systems and have opinions about observability You're drawn to early-stage environments where you own the whole problem Bonus points: Experience with Temporal, Airflow, or similar workflow engines Background in scaling search (Elastic, Qdrant, Pinecone, Weaviate) Familiarity with LLM inference What we offer Customers including one of the world's leading AI labs Competitive salary (€80K–€100K) with meaningful equity (0.25%–0.75%) Health, dental, and vision coverage Work in-person in the heart of Amsterdam (Herengracht) with a highly-skilled, technical team Direct impact on architecture and infrastructure decisions from the first week

We're looking for a founding engineer to own Airweave's data and infrastructure layer, the systems that make our distributed search and data pipelines scalable, reliable and observable. At Airweave, you'll build and operate the platform that thousands of AI agents depend on. That means distributed sync pipelines pulling data from dozens of sources, vector databases powering LLM search, and the orchestration layer that keeps it all running. You'll work closely with the product team, but your focus is on the foundation: making sure data flows reliably at scale, LLM inference stays fast, and the whole system holds up under real production load. This is early-stage infrastructure work. The architecture is still being shaped, and your decisions will define how we scale. What you'll work on Design and scale distributed data pipelines that sync hundreds of millions of documents from dozens sources into advanced search indexes Build and improve Temporal workflows for parallel sync orchestration: retries, backpressure, and failure recovery across workers Own our Kubernetes deployments with Helm charts: autoscaling, and resource management for bursty search, sync and LLM workloads Scale PostgreSQL for high-throughput; connection pooling, read replicas, partitioning (we ask a lot from this database) Manage vector database (Vespa) infrastructure: sharding, replication, backup strategies for large-scale agentic search Orchestrate and optimize LLM inference pipelines: batching, caching, provider failover Build monitoring and alerting with Prometheus, Grafana, and custom instrumentation for cluster health Infrastructure as code for the base with Terraform You might be a fit if You've built or operated data pipelines at scale: ETL, event processing, streaming, or sync infrastructure You're comfortable with Kubernetes, Terraform, and infrastructure as code You've scaled databases and understand the tradeoffs (pooling, replication, sharding) You have experience with distributed systems: workflow orchestration, message queues, eventual consistency You're interested in LLM infrastructure: embeddings, vector search, inference optimization You like building reliable systems and have opinions about observability You're drawn to early-stage environments where you own the whole problem Bonus points: Experience with Temporal, Airflow, or similar workflow engines Background in scaling search (Elastic, Qdrant, Pinecone, Weaviate) Familiarity with LLM inference What we offer Customers including one of the world's leading AI labs Competitive salary ($120K–$160K) with meaningful equity (0.25%–1.00%) Health, dental, and vision coverage Work in-person in San Francisco with a highly-skilled, technical team Direct impact on architecture and infrastructure decisions from the first week

We're looking for a full-stack founding engineer to help build Airweave's product layer that connects AI to user data. At Airweave, you'll work across the entire system: from the search pipelines that power AI agents, to the sync infrastructure that keeps data flowing, to the APIs, MCPs and frontend that developers use every day. You'll ship features that land in production the same day. This is early-stage work. The codebase is young, the architecture is evolving, and your decisions will shape how thousands of AI agents access information. --- What you'll work on Build and improve our multi-step, multi-index, distributed LLM search infrastructure Design and maintain our microservices layer: APIs, MCP servers, and async workers coordinated through Temporal and Redis Extend the sync engine that connects to dozens of sources and keeps data flowing reliably Ship frontend features in React/TypeScript that make complex workflows feel simple Contribute to CI/CD, observability, and the tooling that keeps the team moving fast You might be a fit if You've built and shipped applications end-to-end You like understanding how systems fit together, not just your slice You're comfortable moving between frontend and backend work You have familiarity with transformers, embeddings and vector search You've worked with async Python, TypeScript, or similar You're drawn to early-stage environments where things move fast and change often Bonus Points Experience with data pipelines, infrastructure (Terraform, Kubernetes), or ETL systems Background in distributed systems or workflow orchestration --- What We Offer Customers including one of the world's leading AI labs Competitive salary (€80K–€100K) with meaningful equity (0.25%–0.75%) Health, dental, and vision coverage Work in-person in the heart of Amsterdam (Herengracht) with a highly-skilled, technical team Direct impact on architecture and product direction from the first week

We're looking for a full-stack founding engineer to help build Airweave's product layer that connects AI to user data. At Airweave, you'll work across the entire system: from the search pipelines that power AI agents, to the sync infrastructure that keeps data flowing, to the APIs, MCPs, and frontend that developers use every day. You'll ship features that land in production the same day. This is early-stage work. The codebase is young, the architecture is evolving, and your decisions will shape how thousands of AI agents access information. What you'll work on Build and improve our multi-step, multi-index, distributed LLM search infrastructure Design and maintain our microservices layer: APIs, MCP servers, and async workers coordinated through Temporal and Redis Extend the sync engine that connects to dozens of sources and keeps data flowing reliably Ship frontend features in React/TypeScript that make complex workflows feel simple Contribute to CI/CD, observability, and the tooling that keeps the team moving fast You might be a fit if You've built and shipped applications end-to-end You like understanding how systems fit together, not just your slice You're comfortable moving between frontend and backend work You have familiarity with transformers, embeddings, and information retrieval You've worked with async Python, TypeScript, or similar You know how to productionize your work using Git, CI/CD, and Docker You're drawn to early-stage environments where things move fast and change often Bonus Points Experience with data pipelines, infrastructure (Terraform, Kubernetes), or ETL systems Background in distributed systems or workflow orchestration What We Offer Customers including one of the world's leading AI labs Competitive salary ($120K–$160K) with meaningful equity (0.25%-1.00%) Health, dental, and vision coverage Work in-person in San Francisco with a highly-skilled, technical team Direct impact on architecture and product direction from the first week